Central quantum supercomputer could redefine materials science
Insider Brief: Quantum-centric supercomputers combine quantum and classical systems to tackle computational challenges in materials science, bypassing the memory limitations that hamper classical approaches. Specialized algorithms, such as the variational quantum eigensolver, quantum phase estimation, and Trotterization, can provide accurate modeling of atomic-level properties needed for applications in energy storage, aerospace, and durable materials. Quantum … Read more
